This subproject is one of many research subprojects utilizing theresources provided by a Center grant funded by NIH/NCRR. The subproject andinvestigator (PI) may have received primary funding from another NIH source,and thus could be represented in other CRISP entries. The institution listed isfor the Center, which is not necessarily the institution for the investigator.Scientific Rationale: Aldosterone excess may be a more common cause of or contributing factor to hypertension than previously known with reported prevalence rates of 8-32% depending on the patient population being screened. The standard method of diagnosing aldosterone excess is the measurement of urinary aldosterone excretion rate (UAER) by radioimmunoassay of a timed 24 hour urine collection; however, determination of aldosterone concentration in a random urine specimen (RUS) would be more practical and convenient. The accuracy of the RUS to diagnose aldosterone excess is unknown. The accuracy of albumin and protein measurements in RUS compared to those in timed urine collection (overnight or 24 hour) has been demonstrated. Using a similar approach, we seek to determine the performance of aldosterone measurement in RUS for the diagnosis of aldosterone excess.
Specific Aims : 1) To assess the performance of measurements of urinary aldosterone concentration (UAC) and urinary aldosterone:creatinine ratio (UACR) in a random urine specimen (RUS) in predicting excess urinary aldosterone excretion. 2) To gather preliminary data for the support of an RO1-type application assessing urinary aldosterone excretion in the REasons for Geographic And Racial Differences in Stroke (REGARDS) cohort.Long-term Aims: 1) To assess the degree to which geographic or racial differences in hypertension prevalence and severity are attributable to geographic or racial variations in urinary aldosterone excretion. 2) To assess the degree to which geographic or racial differences in stroke incidence and case fatality are attributable to geographic or racial variations in urinary aldosterone excretion.Methods: Hypertensive volunteers aged 19 years and older (80 participants with complete data needed) will be recruited from the UAB Kirklin Clinic Hypertension Clinic. Normotensive (control) volunteers aged 19 years and older (26 participants with complete data needed) will be recruited from the UAB Sleep/Wake Disorders Center. RUSs will be collected during the morning after completing timed 24 hour urine collections. Aldosterone (measured by radioimmunoassay), sodium, potassium and creatinine will be measured in both the RUS and timed 24 hour urine collections. Urinary samples will be classified as normal or elevated aldosterone according to measured UAER (criteria based on sodium levels). Correlation coefficients will be calculated to determine the relationship between UAER vs. UAC and UACR in subjects with normal or high urinary aldosterone (by UAER) respectively in the hypertensive group and in subjects with normal urinary aldosterone (by UAER) in the control group. The receiver operating characteristics (ROC) curve approach will be used to analyze the performance of the RUS measurements (UAC and UACR) in the diagnosis of excess urinary aldosterone. Bland-Altman plots will be generated to describe the agreement between the two quantitative urinary measurements. The GCRC Biostatistical Core will perform all statistical analyses. Anticipated Impact: The determination of the accuracy of RUS in diagnosing aldosterone excess will improve the ability to screen for this disorder. The preliminary data will be used to support an RO1-type application assessing the degree to which geographic or racial differences in hypertension and stroke are attributable to geographic or racial variations in urinary aldosterone excretion in the REGARDS cohort.
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